Code
class(airquality)[1] "data.frame"
Code
airquality_with_missingvalues <<- airquality[
is.na(airquality$Ozone) | is.na(airquality$Solar.R) |
is.na(airquality$Wind) | is.na(airquality$Temp) |
is.na(airquality$Month) | is.na(airquality$Day),]
print(airquality_with_missingvalues) Ozone Solar.R Wind Temp Month Day
5 NA NA 14.3 56 5 5
6 28 NA 14.9 66 5 6
10 NA 194 8.6 69 5 10
11 7 NA 6.9 74 5 11
25 NA 66 16.6 57 5 25
26 NA 266 14.9 58 5 26
27 NA NA 8.0 57 5 27
32 NA 286 8.6 78 6 1
33 NA 287 9.7 74 6 2
34 NA 242 16.1 67 6 3
35 NA 186 9.2 84 6 4
36 NA 220 8.6 85 6 5
37 NA 264 14.3 79 6 6
39 NA 273 6.9 87 6 8
42 NA 259 10.9 93 6 11
43 NA 250 9.2 92 6 12
45 NA 332 13.8 80 6 14
46 NA 322 11.5 79 6 15
52 NA 150 6.3 77 6 21
53 NA 59 1.7 76 6 22
54 NA 91 4.6 76 6 23
55 NA 250 6.3 76 6 24
56 NA 135 8.0 75 6 25
57 NA 127 8.0 78 6 26
58 NA 47 10.3 73 6 27
59 NA 98 11.5 80 6 28
60 NA 31 14.9 77 6 29
61 NA 138 8.0 83 6 30
65 NA 101 10.9 84 7 4
72 NA 139 8.6 82 7 11
75 NA 291 14.9 91 7 14
83 NA 258 9.7 81 7 22
84 NA 295 11.5 82 7 23
96 78 NA 6.9 86 8 4
97 35 NA 7.4 85 8 5
98 66 NA 4.6 87 8 6
102 NA 222 8.6 92 8 10
103 NA 137 11.5 86 8 11
107 NA 64 11.5 79 8 15
115 NA 255 12.6 75 8 23
119 NA 153 5.7 88 8 27
150 NA 145 13.2 77 9 27
Code
write.csv(airquality_with_missingvalues, file = "_raw_data/airquality_with_missingvalues.csv") #saving our manipulated data